Artificial Intelligence

Unlike earlier tools that generate static content, World Models learn the rules of reality, predicting physics, cause-and-effect, and interactions.

As AI moves from generating code to taking real actions, MCP provides a crucial safety net - but only if developers enforce strict controls and monitor every move.

AI will happily dive in and try to do everything you ask - but just like a mischievous dog, it sometimes gets it spectacularly wrong, warned Atlassian’s Dugald Morrow.

Developers still have agency, but now they also have smarter tools. The question is: are they using them wisely?

As AI coding assistants level up from autocomplete to autonomous, the real challenge isn’t what they can do - it’s how we use them wisely.

It’s no longer about fixing syntax errors - it’s about figuring out why a billion-parameter model did something totally unexpected.

After months of work, your AI agent can run tasks, create content, even make decisions. Exciting - but how do you use it safely and effectively in the real world?

AI moves faster than your last commit - and so do hackers. Security can’t be an afterthought; it has to run alongside your code, like invisible, always-on seatbelts keeping users safe.

What if your AI assistant could juggle flights, messages, and security checks all at once? Filip Srnec showed it’s possible.

Meet AgentKit, OpenAI’s drag-and-drop playground that handles all the boring LLM wiring for you.

Gone are the days of babysitting your AI. As Gift Egwuenu showed at Infobip Shift, agents now think and act for themselves - planning, booking, and getting things done.

You finally built that AI agent. It writes code, drafts emails, maybe even runs tasks on its own. It’s powerful, useful - and ready to ship. But then reality hits: how do you actually price something like this?

The logic behind a simple game of 'Guess Who?' is identical to how we code one of the most transparent AI algorithms. In Decision Trees, we don’t guess - we ask the question that gives the most information, and mastering that intuition teaches the core of predictive Machine Learning